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Python: [BREAKING] updated structure and samples (#875)

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* updated structure and samples

* updated names and removed cross tests

* updated projects etc

* updated tests

* updated test

* test fixes

* removed devui for now

* updated all-tests task

* removed old style configs

* remove coverage from tests

* updated to unit tests with all-tests

* updated foundry everywhere

* fix azure ai tests

* fix merge tests

* fix mypy
This commit is contained in:
Eduard van Valkenburg
2025-09-25 09:02:53 +02:00
committed by GitHub
Unverified
parent 366a7f7d47
commit 9355329dfd
169 changed files with 1159 additions and 1761 deletions
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python/samples/getting_started/workflow/agents/foundry_chat_agents_streaming.py → python/samples/getting_started/workflow/agents/azure_ai_agents_streaming.py
+6 -6
View File
@@ -6,7 +6,7 @@ from contextlib import AsyncExitStack
from typing import Any
from agent_framework import AgentRunUpdateEvent, WorkflowBuilder, WorkflowOutputEvent
from agent_framework.foundry import FoundryChatClient
from agent_framework.azure import AzureAIAgentClient
from azure.identity.aio import AzureCliCredential
"""
@@ -24,21 +24,21 @@ Demonstrate:
- The workflow completes when idle and outputs are available in events.get_outputs().
Prerequisites:
- Foundry Agent Service configured, along with the required environment variables.
- Azure AI Agent Service configured, along with the required environment variables.
- Authentication via azure-identity. Use AzureCliCredential and run az login before executing the sample.
- Basic familiarity with WorkflowBuilder, edges, events, and streaming runs.
"""
async def create_foundry_agent() -> tuple[Callable[..., Awaitable[Any]], Callable[[], Awaitable[None]]]:
"""Helper method to create a Foundry agent factory and a close function.
async def create_azure_ai_agent() -> tuple[Callable[..., Awaitable[Any]], Callable[[], Awaitable[None]]]:
"""Helper method to create a Azure AI agent factory and a close function.
This makes sure the async context managers are properly handled.
"""
stack = AsyncExitStack()
cred = await stack.enter_async_context(AzureCliCredential())
client = await stack.enter_async_context(FoundryChatClient(async_credential=cred))
client = await stack.enter_async_context(AzureAIAgentClient(async_credential=cred))
async def agent(**kwargs: Any) -> Any:
return await stack.enter_async_context(client.create_agent(**kwargs))
@@ -50,7 +50,7 @@ async def create_foundry_agent() -> tuple[Callable[..., Awaitable[Any]], Callabl
async def main() -> None:
agent, close = await create_foundry_agent()
agent, close = await create_azure_ai_agent()
try:
writer = await agent(
name="Writer",
python/samples/getting_started/workflow/agents/azure_chat_agents_streaming.py
+3 -3
View File
@@ -3,7 +3,7 @@
import asyncio
from agent_framework import AgentRunUpdateEvent, WorkflowBuilder, WorkflowOutputEvent
from agent_framework.azure import AzureChatClient
from agent_framework.azure import AzureOpenAIChatClient
from azure.identity import AzureCliCredential
"""
@@ -21,7 +21,7 @@ Demonstrate:
- The workflow completes when idle and outputs are available in events.get_outputs().
Prerequisites:
- Azure OpenAI configured for AzureChatClient with required environment variables.
- Azure OpenAI configured for AzureOpenAIChatClient with required environment variables.
- Authentication via azure-identity. Use AzureCliCredential and run az login before executing the sample.
- Basic familiarity with WorkflowBuilder, edges, events, and streaming runs.
"""
@@ -30,7 +30,7 @@ Prerequisites:
async def main():
"""Build and run a simple two node agent workflow: Writer then Reviewer."""
# Create the Azure chat client. AzureCliCredential uses your current az login.
chat_client = AzureChatClient(credential=AzureCliCredential())
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
# Define two domain specific chat agents. The builder will wrap these as executors.
writer_agent = chat_client.create_agent(
python/samples/getting_started/workflow/agents/custom_agent_executors.py
+7 -7
View File
@@ -10,7 +10,7 @@ from agent_framework import (
WorkflowContext,
handler,
)
from agent_framework.azure import AzureChatClient
from agent_framework.azure import AzureOpenAIChatClient
from azure.identity import AzureCliCredential
"""
@@ -20,12 +20,12 @@ This sample uses two custom executors. A Writer agent creates or edits content,
then hands the conversation to a Reviewer agent which evaluates and finalizes the result.
Purpose:
Show how to wrap chat agents created by AzureChatClient inside workflow executors. Demonstrate the @handler pattern
Show how to wrap chat agents created by AzureOpenAIChatClient inside workflow executors. Demonstrate the @handler pattern
with typed inputs and typed WorkflowContext[T] outputs, connect executors with the fluent WorkflowBuilder, and finish
by yielding outputs from the terminal node.
Prerequisites:
- Azure OpenAI configured for AzureChatClient with required environment variables.
- Azure OpenAI configured for AzureOpenAIChatClient with required environment variables.
- Authentication via azure-identity. Use AzureCliCredential and run az login before executing the sample.
- Basic familiarity with WorkflowBuilder, executors, edges, events, and streaming or non streaming runs.
"""
@@ -41,8 +41,8 @@ class Writer(Executor):
agent: ChatAgent
def __init__(self, chat_client: AzureChatClient, id: str = "writer"):
# Create a domain specific agent using your configured AzureChatClient.
def __init__(self, chat_client: AzureOpenAIChatClient, id: str = "writer"):
# Create a domain specific agent using your configured AzureOpenAIChatClient.
agent = chat_client.create_agent(
instructions=(
"You are an excellent content writer. You create new content and edit contents based on the feedback."
@@ -83,7 +83,7 @@ class Reviewer(Executor):
agent: ChatAgent
def __init__(self, chat_client: AzureChatClient, id: str = "reviewer"):
def __init__(self, chat_client: AzureOpenAIChatClient, id: str = "reviewer"):
# Create a domain specific agent that evaluates and refines content.
agent = chat_client.create_agent(
instructions=(
@@ -106,7 +106,7 @@ class Reviewer(Executor):
async def main():
"""Build and run a simple two node agent workflow: Writer then Reviewer."""
# Create the Azure chat client. AzureCliCredential uses your current az login.
chat_client = AzureChatClient(credential=AzureCliCredential())
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
# Instantiate the two agent backed executors.
writer = Writer(chat_client)